How smart is Apple’s artificial intelligence? We may be about to find out. Earlier this week, the firm announced it would be publishing journal articles about its work in the field and spending time talking to academics.

That’s very un-Apple, a company renowned for its closed ecosystem and locked down hardware. But, as Silicon Valley’s gilded tech giants wrangle for AI supremacy, it’s necessary. The reason for Apple’s surprise volte-face? Elon Musk. His OpenAI project, founded in December 2011, has a $1 billion endowment behind it and has pledged to make nearly all its research and patents open to the public. Earlier this month, the non-profit announced it was releasing its algorithmic training ground, called Universe, to the public.

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DeepMind, the London-based AI company owned by Google parent company Alphabet, has also opened up its AI. The DeepMind Lab, a fully 3D game-like system tailored for training AIs, is now available on GitHub. It’s an impressive gesture, but perhaps not as altruistic as it appears. When you’re trying to “solve intelligence”, you need to hire intelligence.

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Which brings us back to Apple. In a presentation at the annual Neural Information Processing Systems conference (or Nips) Russ Salakhutdinov, director of AI research at Apple, announced that Apple’s machine learning team would both publish its research and engage with academia.

Artificial intelligence will form the mesh on which the world of the future will rely. For the world’s biggest technology companies – the Apples, Googles, Facebooks and Microsofts, it’s an opportunity for revenue and influence that can’t be missed. But, unlike many of the challenges these companies have overcome down the years, it’s also an academic challenge.

Apple’s hiring of Salakhutdinov, who is also a professor in machine learning at Carnegie Mellon University in Pennsylvania, is recognition of this. As such, artificial intelligence is rapidly becoming a collaborative field. And that poses a problem for a traditionally secretive, insular Apple.

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To hire the best AI brains, Apple needs to show its employees can continue to collaborate and openly publish their research with the wider community. That’s especially true if Apple is to make great strides in AI without sacrificing its laser-like focus on privacy. While many machine learning projects rely on vast swathes of data, Apple may decide to focus on Bayesian and evolutionary AI, which could allow computers to learn more like humans by working out systems and ways of doing things from just a few examples, rather than millions.

From the outside, it appears to be playing catch-up against rivals who have embraced AI openness from the off. Torch, an open-source machine learning library released in October 2002, gives Facebook, IBM, Twitter, Yandex and others access to a range of deep machine learning algorithms. In January 2015, Facebook’s Artificial Intelligence Research lab open-sourced a vast trove of modules it had developed for Torch.

The hope, for all the companies trying to win the AI race, is that open-sourcing aspects of their work can save others time and help to speed up the still nascent industry. But, perhaps more importantly, it’s also about attracting the best talent.